arXiv AI By Yaoting Wang, Yun Zhou, Zipei Zhang, Henghui Ding

AVTrack: Audio-Visual Tracking in Human-centric Complex Scenes

Read the original on arXiv AI →

arXiv:2606. 02724v1 Announce Type: cross Abstract: Audio-visual speaker tracking aims to localize and track active speakers by leveraging auditory and visual cues, enabling fine-grained, human-centric scene understanding.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv AI.

arXiv Machine Learning
Jul 14

Empowering Long-form Omni-modal Understanding with Robust Audio Perception

arXiv:2607. 10299v1 Announce Type: new Abstract: Recent advances in large-scale multimodal models have drivenremarkable progress in vision-language tasks; however, comprehensiveomni-modal understanding remains under-explored, largely due to thescarcity of datasets with rich, explicitly aligned auditory cues.

By Kaiying Yan, Luoyi Sun, Xiao Zhou, Weidi Xie
arXiv AI
Jun 18

Revisiting Active Speaker Detection: An In-the-Wild Benchmark for Generalization and Robustness

arXiv:2505. 21954v2 Announce Type: replace-cross Abstract: We present UniTalk, a novel dataset emphasizing challenging scenarios to enhance model generalization for the task of active speaker detection (ASD).

By Le Thien Phuc Nguyen, Zhuoran Yu, Khoa Quang Nhat Cao, Yuwei Guo, Tu Ho Manh Pham, Tuan Tai Nguyen, Toan Ngo Duc Vo, Lucas Poon, Tuan Khai Nguyen, Soochahn Lee, Yong Jae Lee
arXiv AI
Aug 11

Listen, See and Track: Spatio-Temporal Audio-Visual Sound Event Reasoning for Omni-Modal Language Models

arXiv:2608. 09435v1 Announce Type: new Abstract: Understanding dynamic sound sources requires jointly determining what produces a sound, where the source is located, and how it moves over time.

By Zhi Zeng, Cheng Zhang, Zesheng Yang, Rendong Pi, Jiaying Wu, Di Zhang, Zihan Ma, Guodong Li, Zhou Yang, Yu Xiang, Yifei Zheng, Minnan Luo